IEICE TRANSACTIONS on Fundamentals
An Expanded Lateral Interactive Clonal Selection Algorithm and Its Application
Summary :
Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.8 pp.2223-2231
- Publication Date
- 2008/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.8.2223
- Type of Manuscript
- PAPER
- Category
- Neural Networks and Bioengineering
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Shangce GAO, Hongwei DAI, Jianchen ZHANG, Zheng TANG, "An Expanded Lateral Interactive Clonal Selection Algorithm and Its Application" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 8, pp. 2223-2231, August 2008, doi: 10.1093/ietfec/e91-a.8.2223.
Abstract: Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.8.2223/_p
Copy
@ARTICLE{e91-a_8_2223,
author={Shangce GAO, Hongwei DAI, Jianchen ZHANG, Zheng TANG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Expanded Lateral Interactive Clonal Selection Algorithm and Its Application},
year={2008},
volume={E91-A},
number={8},
pages={2223-2231},
abstract={Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.},
keywords={},
doi={10.1093/ietfec/e91-a.8.2223},
ISSN={1745-1337},
month={August},}
Copy
TY - JOUR
TI - An Expanded Lateral Interactive Clonal Selection Algorithm and Its Application
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2223
EP - 2231
AU - Shangce GAO
AU - Hongwei DAI
AU - Jianchen ZHANG
AU - Zheng TANG
PY - 2008
DO - 10.1093/ietfec/e91-a.8.2223
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2008
AB - Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.
ER -
English
